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Targeting Industry Clusters for Regional Economic Development: An Overview of the REDRL Approach

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  • Barkley, David L.
  • Henry, Mark S.

Abstract

An industry cluster is a geographically bounded collection of similar and/or related firms that together create competitive advantages for member firms and the local economy. The targeting of economic development programs at industry clusters provides three principal advantages: multiplier effects are stronger, employment growth potential is enhanced, and new firm spin-offs are promoted. The Clemson University Regional Economic Development Research Laboratory (REDRL) targeting method uses a screening process to identify local industry clusters with high potential for future growth. The region’s industries must pass five screens to be selected as a targeted cluster: substantial local presence as indicated by number of establishments and employees, industry employment in the region is growing, the region is relatively specialized in the industry (LQ> 1.0), and local employment growth exceeds the national industry average. Next, industry value chains are identified to determine if linked industries are good prospects for targeting. Finally, the identified high potential industry clusters are rated according to workers’ wages, potential future employment growth, import substitution potential, average plant size, and linkages to the local economy. Comparisons of these industry characteristics provide communities with insights regarding the potential economic and fiscal impacts associated with the attraction of an establishment in one of the target industries. In summary, the industry cluster targeting approach provides community leaders with (1) a list of industries for which they have a reasonable likelihood of attracting and (2) information regarding the likely benefits and costs associated with each industry. As such, a targeting approach permits communities to use their limited industrial development resources more efficiently to meet their industrial development goals.

Suggested Citation

  • Barkley, David L. & Henry, Mark S., 2005. "Targeting Industry Clusters for Regional Economic Development: An Overview of the REDRL Approach," REDRL Research Reports 113803, Clemson University, Regional Economic Development Research Laboratory (REDRL).
    • Handle: RePEc:ags:curerr:113803
    DOI: 10.22004/ag.econ.113803
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    File URL: https://ageconsearch.umn.edu/record/113803/files/redrl_rpt15.pdf
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    References listed on IDEAS

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    1. Ian R. Gordon & Philip McCann, 2000. "Industrial Clusters: Complexes, Agglomeration and/or Social Networks?," Urban Studies, Urban Studies Journal Limited, vol. 37(3), pages 513-532, March.
    2. David L. Barkley & Mark S. Henry, 1997. "Rural Industrial Development: To Cluster or Not to Cluster?," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 19(2), pages 308-325.
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    Cited by:

    1. Li Fang, 2019. "Manufacturing Clusters and Firm Innovation," Economic Development Quarterly, , vol. 33(1), pages 6-18, February.
    2. Jing Chen & Randall Jackson, 2018. "Regional Industry Cluster Analysis for the Potomac Highlands in West Virginia," Working Papers Resource Document 2018-03, Regional Research Institute, West Virginia University.
    3. Marialuisa Divella & Alessia Lo Turco & Alessandro Sterlacchini, 2023. "Local labour tasks and patenting in US commuting zones," Journal of Economic Geography, Oxford University Press, vol. 23(5), pages 1097-1119.
    4. Thomas E. Lambert & Gary A. Mattson & Kyle Dorriere, 2017. "The impact of growth and innovation clusters on unemployment in US metro regions," Regional Science Policy & Practice, Wiley Blackwell, vol. 9(1), pages 25-37, March.
    5. Hagadone, Todd A. & Grala, Robert K., 2012. "Business clusters in Mississippi's forest products industry," Forest Policy and Economics, Elsevier, vol. 20(C), pages 16-24.
    6. Lo Turco, Alessia & Maggioni, Daniela, 2022. "The knowledge and skill content of production complexity," Research Policy, Elsevier, vol. 51(8).

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